MicroRNA levels quantified in whole blood varies from PBMCs

MicroRNAs are non-coding RNAs that negatively regulate mRNA expression and play significant roles in both health and disease. Differential microRNA expression has been used to aid diagnosis and discriminate disease stages. The accuracy and reliability of microRNA expression measurement is of utmost importance. Quantification of microRNA expression in human peripheral blood is commonly detected using total RNA extracted via different methods. To date, no convincing data are available showing whether microRNA quantification results can be influenced by the use of total RNA extracted from whole blood or peripheral blood mononuclear cells (PBMCs). This study examined miR-146a-5p and miR-155-5p expression using total RNA extracted in parallel from whole blood and PBMCs of 14 healthy volunteers. The data showed that the quantification of miRNA using total RNA extracted from whole blood varied from that of PBMCs, indicating that the miRNA expression was a result of all the different cell-types present in whole blood. Our results suggested that the source of total RNA and the statistical analyses performed are crucial considerations when designing miRNA research.

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MicroRNA levels quantified in whole blood varies from PBMCs

F1000Research ◽

10.12688/f1000research.4884.4 ◽

2015 ◽

Vol 3 ◽

pp. 183

Author(s):

Sadaf Atarod ◽

Hannah Smith ◽

Anne Dickinson ◽

Xiao-Nong Wang

Keyword(s):

Whole Blood ◽

Peripheral Blood ◽

Mononuclear Cells ◽

Human Peripheral Blood ◽

Cell Types ◽

Microrna Expression ◽

Peripheral Blood Mononuclear ◽

Total Rna ◽

Disease Stages ◽

Different Cell Types

MicroRNAs are non-coding RNAs that negatively regulate mRNA expression and play significant roles in both health and disease. Differential microRNA expression has been used to aid diagnosis and discriminate disease stages. The accuracy and reliability of microRNA expression measurement is of utmost importance. Quantification of microRNA expression in human peripheral blood is commonly detected using total RNA extracted via different methods. To date, no convincing data are available showing whether microRNA quantification results can be influenced by the use of total RNA extracted from whole blood or peripheral blood mononuclear cells (PBMCs). This study examined miR-146a-5p and miR-155-5p expression using total RNA extracted in parallel from whole blood and PBMCs of 14 healthy volunteers. The data showed that the quantification of miRNA using total RNA extracted from whole blood varied from that of PBMCs, indicating that the miRNA expression was a result of all the different cell-types present in whole blood. Our results suggested that the source of total RNA and the statistical analyses performed are crucial considerations when designing miRNA research.

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Important considerations for microRNA extraction methods from whole blood and peripheral blood mononuclear cells

F1000Research ◽

10.12688/f1000research.4884.1 ◽

2014 ◽

Vol 3 ◽

pp. 183

Author(s):

Sadaf Atarod ◽

Hannah Smith ◽

Anne Dickinson ◽

Xiao-Nong Wang

Keyword(s):

Peripheral Blood Mononuclear Cells ◽

Whole Blood ◽

Peripheral Blood ◽

Mononuclear Cells ◽

Extraction Methods ◽

Microrna Expression ◽

Peripheral Blood Mononuclear ◽

Total Rna ◽

Expression Levels ◽

Blood Mononuclear Cells

MicroRNAs are non-coding RNAs that negatively regulate mRNA expression and play significant roles in both health and disease. Differential microRNA expression has been used to aid diagnosis and discriminate disease stages. The accuracy and reliability of microRNA expression measurement is of utmost importance. For diagnostic investigations, microRNA expression in human peripheral blood is commonly detected using total RNA extracted using different methods. To date, no convincing data have been available showing whether microRNA expression levels are comparable when total RNA has been extracted from whole blood or peripheral blood mononuclear cells (PBMCs). The present study examined miR-146a-5p and miR-155-5p expression using total RNA extracted in parallel from whole blood and PBMCs of 14 healthy volunteers. MicroRNA expression levels were significantly different between whole blood and PBMCs. No significant difference was observed in microRNA expression between fresh and cryopreserved PBMCs (p=0.125 for both). Further observations revealed that gender differences did not influence miR-146a-5p or miR-155-5p expression regardless of using whole blood(p = 0.797 and 1.00 respectively) or PBMC (p = 0.190 and 0.898 respectively). Our results demonstrate that microRNA expression could be subjective to the methods used for total RNA extraction which highlights the importance of using uniform extraction methods.

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Peripheral blood mononuclear cells preferentially activate 11-oxygenated androgens

Acta Endocrinologica ◽

10.1530/eje-20-1077 ◽

2021 ◽

Vol 184 (3) ◽

pp. 357-367

Author(s):

Lina Schiffer ◽

Alicia Bossey ◽

Punith Kempegowda ◽

Angela E Taylor ◽

Ildem Akerman ◽

...

Keyword(s):

Natural Killer Cells ◽

Natural Killer ◽

Peripheral Blood Mononuclear Cells ◽

Whole Blood ◽

Peripheral Blood ◽

Mononuclear Cells ◽

Human Peripheral Blood ◽

Peripheral Blood Mononuclear ◽

Blood Mononuclear Cells ◽

Timely Fashion

Objective Androgens are important modulators of immune cell function. The local generation of active androgens from circulating precursors is an important mediator of androgen action in peripheral target cells or tissues. We aimed to characterize the activation of classic and 11-oxygenated androgens in human peripheral blood mononuclear cells (PBMCs). Methods PBMCs were isolated from healthy male donors and incubated ex vivo with precursors and active androgens of the classic and 11-oxygenated androgen pathways. Steroids were quantified by liquid chromatography-tandem mass spectrometry. The expression of genes encoding steroid-metabolizing enzymes was assessed by quantitative PCR. Results PBMCs generated eight-fold higher amounts of the active 11-oxygenated androgen 11-ketotestosterone than the classic androgen testosterone from their respective precursors. We identified the enzyme AKR1C3 as the major reductive 17β-hydroxysteroid dehydrogenase in PBMCs responsible for both conversions and found that within the PBMC compartment natural killer cells are the major site of AKRC13 expression and activity. Steroid 5α-reductase type 1 catalyzed the 5α-reduction of classic but not 11-oxygenated androgens in PBMCs. Lag time prior to the separation of cellular components from whole blood increased serum 11-ketotestosterone concentrations in a time-dependent fashion, with significant increases detected from two hours after blood collection. Conclusions 11-Oxygenated androgens are the preferred substrates for androgen activation by AKR1C3 in PBMCs, primarily conveyed by natural killer cell AKR1C3 activity, yielding 11-ketotestosterone the major active androgen in PBMCs. Androgen metabolism by PBMCs can affect the results of serum 11-ketotestosterone measurements, if samples are not separated in a timely fashion. Significance statement We show that human peripheral blood mononuclear cells (PBMCs) preferentially activate 11-ketotestosterone rather than testosterone when incubated with precursors of both the classic and the adrenal-derived 11-oxygenated androgen biosynthesis pathways. We demonstrate that this activity is catalyzed by the enzyme AKR1C3, which we found to primarily reside in natural killer cells, major contributors to the anti-viral immune defense. This potentially links intracrine 11-oxygenated androgen generation to the previously observed decreased NK cell cytotoxicity and increased infection risk in primary adrenal insufficiency. In addition, we show that PBMCs continue to generate 11-ketotestosterone if the cellular component of whole blood samples is not removed in a timely fashion, which could affect measurements of this active androgen in routine clinical biochemistry.

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Transcriptome-Wide Profile of 25-Hydroxyvitamin D3 in Primary Immune Cells from Human Peripheral Blood

Nutrients ◽

10.3390/nu13114100 ◽

2021 ◽

Vol 13 (11) ◽

pp. 4100

Author(s):

Andrea Hanel ◽

Igor Bendik ◽

Carsten Carlberg

Keyword(s):

Vitamin D ◽

Peripheral Blood ◽

Mononuclear Cells ◽

Ex Vivo ◽

Human Peripheral Blood ◽

Cell Types ◽

Physiological Concentration ◽

Peripheral Blood Mononuclear ◽

Dihydroxyvitamin D3 ◽

Interacting Protein

Vitamin D3 is an essential micronutrient mediating pleiotropic effects in multiple tissues and cell types via its metabolite 1α,25-dihydroxyvitamin D3 (1,25(OH)2D3), which activates the transcription factor vitamin D receptor. In this study, we used peripheral blood mononuclear cells (PBMCs) obtained from five healthy adults and investigated transcriptome-wide, whether the precursor of 1,25(OH)2D3, 25-hydroxyvitamin D3 (25(OH)D3), has gene regulatory potential on its own. Applying thresholds of >2 in fold change of gene expression and <0.05 as a false discovery rate, in this ex vivo approach the maximal physiological concentration of 25(OH)D3 (250 nM (nmol/L)) none of the study participants had a significant effect on their PBMC transcriptome. In contrast, 1000 and 10,000 nM 25(OH)D3 regulated 398 and 477 genes, respectively, which is comparable to the 625 genes responding to 10 nM 1,25(OH)2D3. The majority of these genes displayed specificity to the tested individuals, but not to the vitamin D metabolite. Interestingly, the genes MYLIP (myosin regulatory light chain interacting protein) and ABCG1 (ATP binding cassette subfamily G member 1) showed to be specific targets of 10,000 nM 25(OH)D3. In conclusion, 100- and 1000-fold higher 25(OH)D3 concentrations than the reference 10 nM 1,25(OH)2D3 are able to affect the transcriptome of PBMCs with a profile comparable to that of 1,25(OH)2D3.

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Fractional response analysis reveals logarithmic cytokine responses in cellular populations

Nature Communications ◽

10.1038/s41467-021-24449-2 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Karol Nienałtowski ◽

Rachel E. Rigby ◽

Jarosław Walczak ◽

Karolina E. Zakrzewska ◽

Edyta Głów ◽

...

Keyword(s):

Single Cell ◽

Mononuclear Cells ◽

Human Peripheral Blood ◽

Cell Types ◽

Response Analysis ◽

Type I ◽

Peripheral Blood Mononuclear ◽

Fractional Response ◽

Different Cell Types ◽

Cell Data

AbstractAlthough we can now measure single-cell signaling responses with multivariate, high-throughput techniques our ability to interpret such measurements is still limited. Even interpretation of dose–response based on single-cell data is not straightforward: signaling responses can differ significantly between cells, encompass multiple signaling effectors, and have dynamic character. Here, we use probabilistic modeling and information-theory to introduce fractional response analysis (FRA), which quantifies changes in fractions of cells with given response levels. FRA can be universally performed for heterogeneous, multivariate, and dynamic measurements and, as we demonstrate, quantifies otherwise hidden patterns in single-cell data. In particular, we show that fractional responses to type I interferon in human peripheral blood mononuclear cells are very similar across different cell types, despite significant differences in mean or median responses and degrees of cell-to-cell heterogeneity. Further, we demonstrate that fractional responses to cytokines scale linearly with the log of the cytokine dose, which uncovers that heterogeneous cellular populations are sensitive to fold-changes in the dose, as opposed to additive changes.

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Fractional response analysis reveals logarithmic cytokine responses in cellular populations

10.1101/2020.12.08.413468 ◽

2020 ◽

Author(s):

Karol Nienałtowski ◽

Rachel E. Rigby ◽

Jarosław Walczak ◽

Karolina E. Zakrzewska ◽

Jan Rehwinkel ◽

...

Keyword(s):

Single Cell ◽

Mononuclear Cells ◽

Human Peripheral Blood ◽

Cell Types ◽

Response Analysis ◽

Type I ◽

Peripheral Blood Mononuclear ◽

Fractional Response ◽

Different Cell Types ◽

Cell Data

ABSTRACTAlthough we can now measure single-cell signaling responses with multivariate, high-throughput techniques our ability to interpret such measurements is still limited. Even interpretation of dose-response based on single-cell data is not straightforward: signaling responses can differ significantly between cells, encompass multiple signaling effectors, and have dynamic character. Here, we use probabilistic modeling and information-theory to introduce fractional response analysis (FRA), which quantifies changes in fractions of cells with given response levels. FRA can be universally performed for heterogeneous, multivariate, and dynamic measurements and, as we demonstrate, uncovers otherwise hidden patterns in single-cell data. In particular, we show that fractional responses to type I interferon in human peripheral blood mononuclear cells are very similar across different cell types, despite significant differences in mean or median responses and degrees of cell-to-cell heterogeneity. Further, we demonstrate that fractional responses to cytokines scale linearly with the log of the cytokine dose, which uncovers that cellular populations are sensitive to fold-changes in the dose, as opposed to additive changes.

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